Generative versus Discriminative Models for Statistical Left-Corner Parsing

James Henderson


Abstract
We propose two statistical left-corner parsers and investigate their accuracy at varying speeds. The parser based on a generative probability model achieves state-of-the-art accuracy when sufficient time is available, but when high speed is required the parser based on a discriminative probability model performs better. Neural network probability estimation is used to handle conditioning on both the unbounded parse histories and the unbounded lookahead strings.
Anthology ID:
W03-3011
Volume:
Proceedings of the Eighth International Conference on Parsing Technologies
Month:
April
Year:
2003
Address:
Nancy, France
Venues:
IWPT | WS
SIG:
SIGPARSE
Publisher:
Note:
Pages:
115–126
Language:
URL:
https://www.aclweb.org/anthology/W03-3011
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/W03-3011.pdf